Systematic calculation of the surface excitation parameters for 22 materials

Da, Bo; Sun, Yang; Mao, Shifeng; Ding, Zejun

doi:10.1002/sia.5164

Cited by 12 publications

(7 citation statements)

References 42 publications

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“…It is worth noting that the SEP calculated here refers to double surface crossing, with a higher contribution from electrons entering Si as compared with electrons exiting Si. While a comparison with previous literature data is difficult, because different definitions for the SEP were used in the past, our results quite agree with recent data based on the same SEP definition used here.…”

Section: Resultsmentioning

confidence: 99%

Momentum transfer effects in near surface electron energy loss

Calliari

Fanchenko

2015

Surface & Interface Analysis

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We examine two formulations for the differential surface excitation parameter (DSEP): one provided by Tung et al. and the other given by the Chen–Kwei position‐dependent differential inverse inelastic mean free path integrated over the electron trajectory. We demonstrate that the latter converges to the former provided that the dielectric function of the solid does not depend on the momentum transfer or it depends on just the momentum transfer component parallel to the surface. Tung's DSEP represents therefore an approximation to the Chen–Kwei DSEP calculated for a dielectric function with no restrictions on the momentum dependence. The approximation is shown to work in the limit of small momentum transfer and to imply an error of 4%–5% for electrons traveling through the solid with energy E = 1 keV. Copyright © 2015 John Wiley & Sons, Ltd.

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Section: Resultsmentioning

confidence: 99%

Momentum transfer effects in near surface electron energy loss

Calliari

Fanchenko

2015

Surface & Interface Analysis

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“…Therefore, the surface roughness not only affects elastic peak intensity directly but also indirectly affects through surface excitation. Analogous to the definition of surface excitation parameter, where the reduction of elastic peak intensity by the surface excitation is described by a factor e − SEP , a parameter SRP may be introduced such that the intensity of the elastic peak changes by a factor e − SRP due to surface roughness. Here, to quantify only the direct influence of surface topography on the elastically backscattered electrons without including indirect component through surface excitation, SRP is defined according to the ratio of simulated elastic peak intensities between a rough surface and a planar surface by using the bulk model of electron inelastic scattering, as follows:

SRP = - ln ({italicI}_{b, r} / {italicI}_{b, p})

where I b , r is the simulated elastic peak intensity obtained in our Monte Carlo simulation for a rough surface by considering only bulk excitation and I b , p is the simulated elastic peak intensity obtained in our Monte Carlo simulation for a planar surface by considering only bulk excitation.…”

Section: Resultsmentioning

confidence: 99%

Quantification of surface roughness effect on elastically backscattered electrons

Ding

Gong

et al. 2014

Surface & Interface Analysis

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Electron inelastic mean free path can be obtained from a measured elastic peak electron spectroscopy spectrum combined with a Monte Carlo simulation. It is thus necessary to know the influence of various experimental factors to the measured and calculated results. This work investigates the effect of the surface roughness or the surface topography on the intensity of the elastic peak. A Monte Carlo simulation, by taking into account of realistic surface roughness for both Gaussian and non‐Gaussian type rough surfaces experimentally prepared, has been employed to study the surface topography effect. The simulations of elastic peak electron spectroscopy were performed for both planar and rough Al and Cu surfaces and for varied primary energies ranging from 200 to 2000 eV. To quantify the surface roughness effect, the surface roughness parameter is introduced according to the ratio of elastic peak intensities between a rough surface and an ideal planar surface. Simulation results have shown that surface roughness parameter is important in a certain range of emission angle and particularly for large emission angles. For grazing emission, the elastic peak intensity can be largely enhanced by roughness even at nanometer scale. Copyright © 2014 John Wiley & Sons, Ltd.

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“…(3), the surface-excitation feature may still be present to a small extent in the bulk ELF. Because the Begrenzungs effect is important for semiconductors, such as SiO2, especially at small crossing angles, 73 not only the increase of surface excitations but also reduction of volume excitations is significant in this surface-excitation feature. Therefore, the intensity of this peak increases slightly at larger emission angles where stronger surface excitation is expected; meanwhile, the intensity of the bulk excitation peak at $23 eV gradually decreases.…”

Section: Resultsmentioning

confidence: 99%

A reverse Monte Carlo method for deriving optical constants of solids from reflection electron energy-loss spectroscopy spectra

Sun

Mao

et al. 2013

Journal of Applied Physics

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A reverse Monte Carlo (RMC) method is developed to obtain the energy loss function (ELF) and optical constants from a measured reflection electron energy-loss spectroscopy (REELS) spectrum by an iterative Monte Carlo (MC) simulation procedure. The method combines the simulated annealing method, i.e., a Markov chain Monte Carlo (MCMC) sampling of oscillator parameters, surface and bulk excitation weighting factors, and band gap energy, with a conventional MC simulation of electron interaction with solids, which acts as a single step of MCMC sampling in this RMC method. To examine the reliability of this method, we have verified that the output data of the dielectric function are essentially independent of the initial values of the trial parameters, which is a basic property of a MCMC method. The optical constants derived for SiO 2 in the energy loss range of 8-90 eV are in good agreement with other available data, and relevant bulk ELFs are checked by oscillator strength-sum and perfect-screening-sum rules. Our results show that the dielectric function can be obtained by the RMC method even with a wide range of initial trial parameters. The RMC method is thus a general and effective method for determining the optical properties of solids from REELS measurements. V C 2013 AIP Publishing LLC. [http://dx.

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Systematic calculation of the surface excitation parameters for 22 materials

Cited by 12 publications

References 42 publications

Momentum transfer effects in near surface electron energy loss

Momentum transfer effects in near surface electron energy loss

Quantification of surface roughness effect on elastically backscattered electrons

A reverse Monte Carlo method for deriving optical constants of solids from reflection electron energy-loss spectroscopy spectra

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